Systems and methods for vehicle smart seats

ABSTRACT

A method comprises obtaining smart seat sensor data, the smart seat sensor data being detected by a tactile-sensitive surface material of a seat of an autonomous vehicle in response to a user interacting with the tactile-sensitive surface material. Other sensor data is obtained from one or more other sensors disposed within the autonomous vehicle. The smart seat sensor data and the other sensor data are integrated. A behavior of the user is estimated based on the integrated data, and the autonomous vehicle is controlled based on the estimated behavior of the user.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of and priority to U.S. ProvisionalPatent Application No. 62/712,069 filed on Jul. 30, 2018, which ishereby incorporated by reference in its entirety.

TECHNICAL FIELD

This disclosure pertains to autonomous vehicles. More specifically, thisdisclosure pertains to systems and methods related to autonomous vehiclesmart seats.

BACKGROUND

Under some approaches, cameras may be used to capture images of users(e.g., passengers, safety drivers) within an autonomous vehicle.However, such cameras may breach user privacy (e.g., by capturing actualimages of the user), and require large amounts of computing resources(e.g., to store and/or process image data).

SUMMARY

Various embodiments of the present disclosure include systems, methods,and non-transitory computer readable media configured to obtain smartseat sensor data, the smart seat sensor data being detected by atactile-sensitive surface material of a seat of an autonomous vehicle inresponse to a user interacting with the tactile-sensitive surfacematerial. Other sensor data is obtained from one or more other sensorsdisposed within the autonomous vehicle. The smart seat sensor data andthe other sensor data are integrated. A behavior of the user isestimated based on the integrated data, and the autonomous vehicle iscontrolled based on the estimated behavior of the user.

In some embodiments, the user interacting with the tactile-sensitivesurface material comprises a passenger sitting on the seat of theautonomous vehicle.

In some embodiments, the other sensor data comprises any of weight dataand temperature data.

In some embodiments, the behavior of the user is estimated using amachine learning model.

In some embodiments, the estimated behavior comprises any of the userentering the autonomous vehicle, the user exiting the autonomousvehicle, the user damaging the autonomous vehicle, and the user leavingan object in the autonomous vehicle subsequent to the user exiting theautonomous vehicle.

In some embodiments, the one or more other sensors are disposed withinany of a headrest portion of the seat of the autonomous vehicle, abackrest portion of the seat, a sitting portion of the seat of theautonomous vehicle, a floor portion of the autonomous vehicle, a roofportion of the autonomous vehicle, and a door portion of the autonomousvehicle. In related embodiments, the integrating the smart seat sensordata and the other sensor data includes creating a new dataset inaccordance with the machine learning model.

In some embodiments, the controlling the autonomous vehicle comprisesany allowing the autonomous vehicle to perform one or more autonomousvehicle actions, and preventing the autonomous vehicle from performingone or more autonomous vehicle actions. In related embodiments, the oneor more autonomous vehicle action include any of accelerating, braking,turning an engine of the autonomous vehicle off, and turning the engineof the autonomous vehicle on.

Various embodiments of the present disclosure include systems, methods,and non-transitory computer readable media configured to obtainautonomous vehicle sensor data of an autonomous vehicle. One or moreautonomous vehicle actions of the autonomous vehicle are predicted basedon the autonomous vehicle sensor data. Interactive content is identifiedfrom a library of interactive content. The interactive content isadjusted based on the predicted one or more autonomous vehicle actions,and the adjusted interactive content is presented within the autonomousvehicle.

In some embodiments, the one or more autonomous vehicle actions includeany of steering, accelerating, and braking.

In some embodiments, the adjusting the interactive content comprisesadjusting a playback speed of the interactive content.

In some embodiments, the adjusting the interactive content comprisesrotating at least a portion of the interactive content.

In some embodiments, the presenting the adjusted interactive contentwithin the autonomous vehicle comprises projecting the interactivecontent on an interior surface of the autonomous vehicle.

In some embodiments, the surface comprises a curved interior surface. Inrelated embodiments, the curved interior surface comprises a window ofthe autonomous vehicle. In related embodiments, the interactive contentis projected from a projector mounted within the autonomous vehicle.

In some embodiments, the systems, methods, and non-transitory computerreadable media further configured to estimating a behavior of a userbased on smart seat sensor data detected by a tactile-sensitive surfacematerial of a seat of the autonomous vehicle; and adjusting theinteractive content in response to the estimated user behavior.

These and other features of the systems, methods, and non-transitorycomputer readable media disclosed herein, as well as the methods ofoperation and functions of the related elements of structure and thecombination of parts and economies of manufacture, will become moreapparent upon consideration of the following description and theappended claims with reference to the accompanying drawings, all ofwhich form a part of this specification, wherein like reference numeralsdesignate corresponding parts in the various figures. It is to beexpressly understood, however, that the drawings are for purposes ofillustration and description only and are not intended as a definitionof the limits of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a diagram of an example system for detecting userbehavior within an autonomous vehicle, and presenting interactivecontent within an autonomous vehicle according to some embodiments.

FIG. 2 depicts a diagram of an example of a smart seat system accordingto some embodiments.

FIG. 3 depicts a diagram of an example of an autonomous vehicleinteractive content presentation system according to some embodiments.

FIG. 4 depicts a flowchart of an example of a method of detecting userbehavior within an autonomous vehicle according to some embodiments.

FIG. 5 depicts a flowchart of an example of a method of presentinginteractive content within an autonomous vehicle according to someembodiments.

FIG. 6 depicts a flowchart of an example of a method of detecting userbehavior within an autonomous vehicle and presenting interactive contentwithin an autonomous vehicle according to some embodiments.

FIG. 7 depicts a diagram of an example of an autonomous vehicleaccording to some embodiments.

FIGS. 8A-C depict diagrams of a seating compartment of an autonomousvehicle configured to present interactive content on an interior surfaceof the autonomous vehicle.

FIGS. 9 depicts a diagram of a seating compartment of an autonomousvehicle configured to detect user behavior within the autonomousvehicle.

FIG. 10 depicts a diagram of a seating compartment of an autonomousvehicle configured to detect user behavior within the autonomous vehicleand present interactive content on an interior surface of the autonomousvehicle.

FIG. 11 is a diagram of an example computer system for implementing thefeatures disclosed herein.

DETAILED DESCRIPTION

A claimed solution rooted in computer technology overcomes problemsspecifically arising in the realm of computer technology. In variousembodiments, a system is configured to detect and/or obtain smart seatsensor data. The smart seat sensor data may be detected by atactile-sensitive surface material of a seat of an autonomous vehicle.For example, the tactile-sensitive surface material may comprise fabricwith electrical properties woven therein. The smart seat sensor data maybe detected in response to a user (e.g., passenger, safety driver)interacting with the tactile-sensitive surface material (e.g., sittingon the tactile-sensitive surface material). The system may detect and/orobtain other sensor data from one or more other sensors (e.g., weightsensors, temperature sensors) disposed within the autonomous vehicle.The one or more other sensors may be disposed in various portion of theautonomous vehicle (e.g., seat, floor, door, roof). The system mayintegrate the smart seat sensor data and the other sensor data. This mayinclude, for example, normalizing the data and/or preparing the data foruse by one or more machine learning models. Using the integrated thedata, the system may estimate a behavior of the user. This may, forexample, allow the system to determine behaviors of the user withoutrequiring cameras, large amounts of computing resources, and/orbreaching user privacy. In some embodiments, a machine learning modelmay be used to estimate user behavior, such as user being properlyseated on the seat of the autonomous vehicle, a user exiting theautonomous vehicle, a user damaging the autonomous vehicle, a user beingasleep in the autonomous vehicle, and/or the like. The autonomousvehicle may also be controlled based on the estimated behavior of theuser. For example, the autonomous vehicle may be prevented from movingfrom a stop unless the user is seated.

In various embodiments, a system is configured to obtain autonomousvehicle sensor data of an autonomous vehicle. For example, the systemmay control various sensors (e.g., cameras, radar, Lidar) of theautonomous vehicle to detect sensor data. The system may predict one ormore autonomous vehicle actions of the autonomous vehicle based on theautonomous vehicle sensor data (e.g., predicting a steering action basedon sensor data indicating an upcoming turn). The system may identifyinteractive content from a library of interactive content. Theinteractive content may be identified in response to user input, basedon exterior conditions (e.g., terrain, time of day), and/or the like.The interactive content may include virtual reality content, augmentedreality content, projected content, and/or the like. Interactive contentmay include three-dimensional (3D) and/or two-dimensional (2D) images,video, audio, haptics, and/or the like. The system may adjust theinteractive content based on current autonomous vehicle action,predicted autonomous vehicle actions, and/or estimated behavior of auser. The adjusted interactive content may be presented within theautonomous vehicle. For example, the interactive content may be rotatedto correspond with a steering action and/or an upcoming steering action,and the rotated interactive content may be presented on an interiorsurface of the autonomous vehicle (e.g., a window). This may, forexample, provide the user with a more immersive and/or comfortableexperience.

FIG. 1 depicts a diagram 100 of an example system for detecting userbehavior within an autonomous vehicle, and presenting interactivecontent within an autonomous vehicle according to some embodiments. Inthe example of FIG. 1, the system includes an autonomous vehicle 102, anautonomous vehicle smart seat system (or, simply, “smart seat system”)104, an autonomous vehicle interactive content presentation system (or,simply, “interactive content presentation system”) 106, and acommunication network 108. In various embodiments, the systems 104-106and the communication network 110 are implemented as part of theautonomous vehicle 102. The autonomous vehicle 102 may be capable ofsensing its environment and/or navigating with a limited human input orwithout human input. The “vehicle” discussed in this paper typicallyincludes a vehicle that travels on the ground (e.g., car, truck, bus),but may also include a vehicle that travels in the air (e.g., drones,helicopter, airplanes, and so on), travels on water (e.g., a boat),and/or the like. The “vehicle” discussed in this paper may accommodateone or more users (e.g., passengers, safety drivers) therein. An exampleof an autonomous vehicle 102 is depicted in FIG. 7.

In the example of FIG. 1, the autonomous vehicle 102 includes anautonomous vehicle sensor system 110 and an autonomous vehicle controlsystem 112. The autonomous vehicle sensor system 110 may detectautonomous vehicle sensor data 114. In some embodiments, the autonomousvehicle sensor system 110 may include a rotatable laser scanning system.The rotatable laser scanning system may include a laser, scanner andoptics, photodetector and receiver electronics, and position andnavigation systems. The rotatable laser scanning system may projectlight (e.g., pulsed laser light) on regions surrounding an autonomousvehicle (e.g., an autonomous vehicle the rotatable laser scanning systemis mounted on), and measure the reflected pulses. The reflected pulsesmay be used to generate representations (e.g., 3D representations) ofthe regions surrounding the autonomous vehicle. The rotatable laserscanning system may rotate 360 degrees in order to capture sensor datafor the regions surrounding the autonomous vehicle. An example rotatablelaser scanning system 702 in shown in FIG. 7.

In some embodiments, the autonomous vehicle sensor system 110 mayinclude cameras mounted on the autonomous vehicle to capture images (or,image data) of regions surrounding the autonomous vehicle. For example,the cameras may capture images in front of the autonomous vehicle, onthe sides of the autonomous vehicle, above the autonomous vehicle, belowthe autonomous vehicle, and/or behind the autonomous vehicle.

The autonomous vehicle control system 112 may function to processautonomous vehicle sensor data 114 to sense an environment surroundingan autonomous vehicle and/or cause an autonomous vehicle to performand/or predict one or more autonomous vehicle control actions (or,simply, “control actions” or “actions”). For example, the autonomousvehicle control system 112 may analyze sensor data 114 to identifyobjects (e.g., traffic signals, road signs, other vehicles, pedestrians,and obstacles) in one or more regions surrounding the autonomousvehicle. As used herein, control actions may include controllingbraking, acceleration, and/or steering without real time human input.Additionally, control actions may include adjusting components withinthe autonomous vehicle 102 (e.g., rotating seats). Furthermore, as usedherein, “real time human input” is intended to represent a human inputthat is needed to concurrently control wheel movement of anon-self-driving vehicle, such as gear shifting, steering control,braking pedal control, acceleration pedal control, crutch pedal control,and so on. The autonomous vehicle control system 112 may be implementedas a central computing system of an autonomous vehicle.

The smart seat system 104 may function to detect interactions within anautonomous vehicle without requiring a camera and/or other imagingdevices. Interactions may include placing an object (e.g., a box) on aseat of the autonomous vehicle, a user sitting on a seat,opening/closing a door, damaging a portion of the autonomous vehicle(e.g., a seat), and/or the like. In some embodiments, the smart seatsystem 104 includes and/or cooperates with tactile-sensitive surfacematerial within an autonomous vehicle to obtain smart seat sensor data.For example, the tactile-sensitive surface material may comprise fabricembedded with electrical properties (e.g., resistive properties,conductive properties). The smart seat data may be detected in responseto user interaction with the tactile-sensitive surface material. Thetactile-sensitive surface material may disposed on one or more surfacesof the autonomous vehicle, such as seats (e.g., tactile-sensitivesurface material may comprise the outer surface of the seat), doors,floor, ceiling, and/or the like.

In some embodiments, the smart seat system 104 may include and/orcooperate with one or more other sensors in addition to thetactile-sensitive surface material. For example, the other sensors mayinclude weight sensors, temperature sensors, pressure sensors, and/orthe like. The other sensors may disposed within one or more interiorportions of the autonomous vehicle (e.g., seats, floor, ceiling, doors)to detect other sensor data. For example, the other sensors may detecttemperatures and/or changes in temperatures within the autonomousvehicle (e.g., an ambient temperature of the autonomous vehicle) and/orobjects and/or users within the autonomous vehicle. In some embodiments,the smart seat system 104 may detect interactions within the autonomousvehicle based on the smart seat data and the other sensor data.

In some embodiments, the smart seat system 104 may estimate behaviors ofusers and/or objects within an autonomous vehicle. The smart seat system104 may estimate behaviors based on the smart seat data and/or the othersensor data. In some embodiments, the smart seat system 104 may utilizea machine learning model (e.g., a random forest model) to estimatebehaviors within an autonomous vehicle. For example, the smart seatsystem 104 may integrate the smart seat system data and the other sensordata according to a machine learning model, and the machine learningmodel may output one or more estimated behaviors. This may allow, forexample, actions to be taken based on estimated behavior instead ofactual behavior (e.g., as captured by a camera or other device). Thismay, for example, reduce the need for extensive computing resources(e.g., storage for image data, and image processing equipment), as mayhelp maintain user privacy.

The interactive content presentation system 106 may function to presentinteractive content within an autonomous vehicle. Interactive contentmay include virtual reality content, augmented reality content, and/orthe like. In some embodiments, functionality of the interactive contentpresentation system 106 may be performed by one or more projectordevices and/or one or more other computing devices. For example, aprojector may be mounted inside the autonomous vehicle, and project theinteractive content onto one or more interior surfaces of the autonomousvehicle (e.g., windows). In some embodiments, the interior surfaces ofthe autonomous vehicle may be curved in order to facilitate presentationof the interactive content.

In some embodiments, goggles and/or glasses may or more may not berequired to view the interactive content. For example, glasses may beused to view interactive content projected into an interior surface ofthe autonomous vehicle. In some embodiments, the interactive contentpresentation system 106 may function to present interactive contentwithout requiring a projector. For example, the material of the interiorsurface (e.g., window) may comprise an interactive content displaydevice capable of displaying the interactive content.

In some embodiments, the interactive content presentation system 106 mayfunction to adjust a presentation of interactive content. For example,the interactive content presentation system 106 may rotate apresentation of interactive content based on one or more actual orpredicted autonomous vehicle actions, and/or estimated behaviors of auser. For example, the interactive content may be rotated to correspondto a steering action of the autonomous vehicle.

The communications network 108 may represent one or more computernetworks (e.g., LAN, WAN, or the like) or other transmission mediums.The communication network 108 may provide communication between theautonomous vehicle 102, systems 104-106, and/or othersystems/engine/datastores described herein. In some embodiments, thecommunication network 108 includes one or more computing devices,routers, cables, buses, and/or other network topologies (e.g., mesh, andthe like). In some embodiments, the communication network 108 may bewired and/or wireless. In various embodiments, the communication network108 may include the Internet, one or more wide area networks (WANs) orlocal area networks (LANs), one or more networks that may be public,private, IP-based, non-IP based, and so forth.

FIG. 2 depicts a diagram 200 of an example of a smart seat system 104according to some embodiments. In the example of FIG. 2, the smart seatsystem 104 includes a smart seat sensor engine 202, a behaviorestimation engine 204, an activity recording and tracking engine 206, acommunication engine 208, and an autonomous vehicle smart seat systemdatastore 210.

The smart seat sensor engine 204 may function to obtain and/or detectsensor data. The sensor data may include smart seat sensor data 220 andother sensor data 222. Smart seat sensor data 220 may be detected bytactile-sensitive surface material, and the other sensor data may bedetected by one or more other sensors disposed within an autonomousvehicle. Example configurations are shown in FIGS. 9 and 10.

The behavior estimation engine 206 may function to integrate smart seatsensor data 220 and other sensor data 222. For example, the behaviorestimation engine may normalize the data 220-222, create a new dataset,and/or the like. The behavior estimation engine 206 may integrate thedata based on one more machine learning models 228. For example, thedata 220-222 may be integrated according to parameters and/or otherattributes of a machine learning model 228 configured to estimatebehavior of a user.

In some embodiments, the behavior estimation engine 206 may function toestimate behavior of a user. For example, the behavior of the user maybe estimated using a machine learning model 228. For example, themachine learning model 228 may use the integrated data 224 to estimateuser behaviors 226. Estimating behaviors may require less computingresources than capturing images of user behaviors, and may help maintainuser privacy.

The activity recording and tracking engine 206 may function to store,record, and/or track smart seat sensor data 220, other sensor data 220,integrated data 224, and machine learning models 228. In someembodiments, the activity recording and tracking engine 206 may trackbehaviors 226 and notify the users and/or other entities of particularbehaviors. For example, if a user leaves an object (e.g., a wallet) onthe seat of the autonomous vehicle and exits the autonomous vehicle, theactivity recording and tracking engine 206 may send a notification to adevice (e.g., mobile device) associated with the user. Similarly, ifdamage to the autonomous vehicle is estimated to have been caused to theautonomous vehicle by the user, then a device of an owner of theautonomous vehicle may be notified.

The communication engine 208 may function to send requests, transmitand, receive communications, and/or otherwise provide communication withone or a plurality of systems. In some embodiments, the communicationengine 208 functions to encrypt and decrypt communications. Thecommunication engine 208 may function to send requests to and receivedata from one or more systems through a network or a portion of anetwork. Depending upon implementation-specific considerations, thecommunication engine 208 may send requests and receive data through aconnection, all or a portion of which may be a wireless connection. Thecommunication engine 208 may request and receive messages, and/or othercommunications from associated systems. Communications may be stored atleast temporarily (e.g., cached and/or persistently) in the datastore210.

FIG. 3 depicts a diagram 300 of an example of an autonomous vehicleinteractive content presentation system 106 according to someembodiments. In the example of FIG. 3, the interactive contentpresentation system 106 includes an interactive content presentationengine 302, an interactive content adjustment engine 304, acommunication engine 306, and an interactive content presentation systemdatastore 308.

The interactive content presentation engine 302 may function to presentinteractive content 310 within an autonomous vehicle. In someembodiments, the interactive content presentation engine 302 may projectinteractive content 310 on to a surface of the autonomous vehicle (e.g.,a window). For example, an interactive content projector may projectmulti-layered images of the interactive content 310 (or interactivecontent 310 converted into multi-layered images) on to a curved surface(e.g., a window of the autonomous vehicle). In some embodiments, theinteractive content 310 may be presented by the surface itself, asopposed to being projected thereon. For example, the window may comprisean interactive content display device capable of displayingmulti-layered images that present and/or similar virtual reality,augmented reality, and/or the like. The interactive content presentationengine 302 may also include speakers and/or other output devices (e.g.,haptic output devices) or outputting audio, haptics, and/or the like, inaddition to images.

The interactive content adjustment engine 304 may function to adjustinteractive content. The interactive content adjustment engine 304 mayadjust interactive content in real-time (e.g., as it is being playedback), and/or prior to playback. In some embodiments, the interactivecontent adjustment engine 304 may adjust interactive content 310 basedon estimated user behaviors, predicted autonomous vehicle actions,and/or the like. For example, the interactive content adjustment engine304 adjust a playback speed of interactive content and/or may rotate acurrently presented interactive content in anticipation of a predictedsteering action the autonomous vehicle.

The communication engine 306 may function to send requests, transmitand, receive communications, and/or otherwise provide communication withone or a plurality of systems. In some embodiments, the communicationengine 306 functions to encrypt and decrypt communications. Thecommunication engine 306 may function to send requests to and receivedata from one or more systems through a network or a portion of anetwork. Depending upon implementation-specific considerations, thecommunication engine 306 may send requests and receive data through aconnection, all or a portion of which may be a wireless connection. Thecommunication engine 306 may request and receive messages, and/or othercommunications from associated systems. Communications may be stored atleast temporarily (e.g., cached and/or persistently) in the datastore308.

FIG. 4 depicts a flowchart 400 of an example of a method of detectinguser behavior within an autonomous vehicle according to someembodiments. In this and other flowcharts, the flowchart 400 illustratesby way of example a sequence of steps. It should be understood the stepsmay be reorganized for parallel execution, or reordered, as applicable.Moreover, some steps that could have been included may have been removedto avoid providing too much information for the sake of clarity and somesteps that were included could be removed, but may have been includedfor the sake of illustrative clarity.

In step 402, a smart seat system (e.g., smart seat system 104) obtainssmart seat sensor data (e.g., smart seat sensor data 220). The smartseat sensor data may be detected by a tactile-sensitive surface material(e.g., tactile-sensitive surface material 904) of a seat (e.g., seat902) of an autonomous vehicle (e.g., autonomous vehicle 102) in responseto a user (e.g., passenger, safety driver) interacting with thetactile-sensitive surface material. For example, a user interacting withthe tactile-sensitive surface material may include a passenger sittingon the seat of the autonomous vehicle.

In some embodiments, a smart seat sensor engine (e.g., smart seat sensorengine 202) obtains and detects the smart seat sensor data. The smartseat sensor data may be recorded. For example, an activity recording andtracking engine (e.g., activity recording and tracking engine 208) mayrecord the smart seat sensor data in a datastore (e.g., autonomousvehicle smart seat system datastore 210).

In step 404, the smart seat system obtains other sensor data (e.g.,other sensor data 222) from one or more other sensors (e.g., sensor 912)disposed within the autonomous vehicle. For example, the other sensordata may include weight data, temperature data, and/or the like. In someembodiments, the one or more other sensors are disposed within aheadrest portion of the seat of the autonomous vehicle, a backrestportion of the seat, a sitting portion of the seat of the autonomousvehicle, a floor portion of the autonomous vehicle, a roof portion ofthe autonomous vehicle, and a door portion of the autonomous vehicle. Insome embodiments, the smart seat sensor engine obtains and/or detectsthe other sensor data. The other sensor data may be recorded. Forexample, the activity recording and tracking engine may record the othersensor data in the datastore.

In step 406, the smart seat system integrates the smart seat sensor dataand the other sensor data. In some embodiments, the smart seat sensordata and the other sensor data may be integrated to create a new datasetin accordance with the machine learning model. For example, the machinelearning model may require the input data to conform to a particularformat (e.g., a particular normalized format).

In some embodiments, a behavior estimation engine (e.g., behaviorestimation engine 204) integrates the smart seat sensor data and theother sensor data. The integrated data (e.g., integrated data 224) maybe recorded. For example, the activity recording and tracking engine mayrecord the integrated data in the datastore.

In step 408, the smart seat system estimates a behavior (e.g., estimatedbehaviors 226) of a user based on the integrated data. For example, thebehavior of the user may be estimated using a machine learning model(e.g., machine learning model 228). In some embodiments, the behaviorestimation engine estimates the behavior of the user. The behavior datamay be recorded. For example, the activity recording and tracking enginemay record the behavior data in the datastore. In some embodiments,behaviors may include a passenger buckling a seat belt, leaving anobject on the seat of the autonomous vehicle, exiting the autonomousvehicle, the damaging the autonomous vehicle (e.g., tearing thetactile-sensitive surface material).

In step 410, an autonomous vehicle control system (e.g., autonomousvehicle control system 112) control the autonomous vehicle based on theestimated behavior of the user. In some embodiments, a communicationengine (e.g., communication engine 208) may provide the estimatebehavior to the autonomous vehicle control system, and autonomousvehicle control system may allow/cause the autonomous vehicle to performone or more autonomous vehicle actions, and/or prevent the autonomousvehicle from performing one or more autonomous vehicle actions. Forexample, autonomous vehicle actions may include accelerating, braking,turning an engine off, and turning the engine on, and/or the like.

FIG. 5 depicts a flowchart 500 of an example of a method of presentinginteractive content within an autonomous vehicle according to someembodiments.

In step 502, an interactive content presentation system (e.g.,autonomous vehicle interactive content presentation system 106) obtainsautonomous vehicle sensor data (e.g., autonomous vehicle sensor data114) of an autonomous vehicle (e.g., autonomous vehicle 102). Forexample, the autonomous vehicle sensor data may be detected by sensorsystem mounts on the autonomous vehicle (e.g., sensor system 702).

In step 504, an autonomous vehicle control system (e.g., autonomousvehicle control system 112) predicts one or more autonomous vehicleactions of the autonomous vehicle based on the autonomous vehicle sensordata. For example, autonomous vehicle actions include steering,accelerating, and/or braking.

In step 506, the interactive content presentation system identifiesinteractive content (e.g., interactive content 310) from a library ofinteractive content (e.g., stored in datastore 308). In someembodiments, an interactive content presentation engine (e.g.,interactive content presentation engine 302) identifies the interactivecontent.

In step 508, the interactive content presentation system adjust theinteractive content based on the predicted one or more autonomousvehicle actions. For example, a playback speed of the interactivecontent be adjusted, the interactive content may be rotated, and/or thelike. In some embodiments, an interactive content adjustment engine(e.g., interactive content adjustment engine 304) adjusts theinteractive content. In some embodiments, the interactive contentpresentation system adjusts the interactive content based on one or moreestimated behaviors of a user instead of, or in addition to, thepredicted one or more autonomous vehicle actions.

In step 510, the interactive content presentation system presents theadjusted interactive content within the autonomous vehicle. For example,the interactive content may be projected (e.g., by an HD laser projectormounted in the autonomous vehicle) on an interior surface (e.g., awindow) of the autonomous vehicle. The surface may be curved (e.g., tofacilitate presentation of the interactive content). In someembodiments, the interactive content presentation engine presents theadjusted interactive content.

FIG. 6 depicts a flowchart 600 of an example of a method of detectinguser behavior within an autonomous vehicle and presenting interactivecontent within an autonomous vehicle according to some embodiments.

In step 602, a smart seat system (e.g., smart seat system 104) obtainssmart seat sensor data (e.g., smart seat sensor data 220). The smartseat sensor data may be detected by a tactile-sensitive surface material(e.g., tactile-sensitive surface material 904) of a seat (e.g., seat902) of an autonomous vehicle (e.g., autonomous vehicle 102) in responseto a user (e.g., passenger, safety driver) interacting with thetactile-sensitive surface material. For example, a user interacting withthe tactile-sensitive surface material may include a passenger sittingon the seat of the autonomous vehicle.

In step 604, an interactive content presentation system (e.g.,autonomous vehicle interactive content presentation system 106) obtainsautonomous vehicle sensor data (e.g., autonomous vehicle sensor data114) of the autonomous vehicle.

In step 606, the smart seat system estimates a behavior (e.g., estimatedbehaviors 226) of a user based on the integrated data. For example, thebehavior of the user may be estimated using a machine learning model(e.g., machine learning model 228). In some embodiments, the behaviorestimation engine estimates the behavior of the user. The behavior datamay be recorded. For example, the activity recording and tracking enginemay record the behavior data in the datastore. In some embodiments,behaviors may include a passenger buckling a seat belt, leaving anobject on the seat of the autonomous vehicle, exiting the autonomousvehicle, the damaging the autonomous vehicle (e.g., tearing thetactile-sensitive surface material).

In step 608, the interactive content presentation system presentsinteractive content (e.g., interactive content 310) within theautonomous vehicle. For example, the interactive content may beprojected (e.g., by an HD laser projector mounted in the autonomousvehicle) on an interior surface (e.g., a window) of the autonomousvehicle. The surface may be curved (e.g., to facilitate presentation ofthe interactive content). In some embodiments, the interactive contentpresentation engine presents the adjusted interactive content.

In step 610, the interactive content presentation system adjusts theinteractive content. For example, the interactive content may beadjusted based on the estimated user behaviors. For example, theestimated user behavior may be sleeping (e.g., based on a particulartype of movement and/or lack of movement detected by thetactile-sensitive surface material). Thus, for example, the interactivecontent playback may be paused/terminated, a brightness of theinteractive content may be reduced, and/or the like. In someembodiments, an interactive content adjustment engine (e.g., interactivecontent adjustment engine 304) adjusts the interactive content. In someembodiments, the interactive content presentation system adjusts theinteractive content based on one or more estimated behaviors of a userinstead of, or in addition to, the predicted one or more autonomousvehicle actions.

In step 612, an autonomous vehicle control system (e.g., autonomousvehicle control system 112) controls the autonomous vehicle. In someembodiments, the autonomous vehicle may be controlled based estimateduser behavior and/or predicted autonomous vehicle actions. For example,the seat of the autonomous vehicle may be adjusted (e.g., rotated)according to a predicted and/or current steering action. Accordingly,when the autonomous vehicle turns, the interactive content may berotated to correspond to the turn, and the seat of the passenger may berotated to correspond to the turn and/or rotated interactive content.This may, for example, reduce motions sickness and/or improve animmersive experience of the user.

In some embodiments, a communication engine (e.g., communication engine208) may provide the estimate behavior to the autonomous vehicle controlsystem, and autonomous vehicle control system may allow/cause theautonomous vehicle to perform one or more autonomous vehicle actions,and/or prevent the autonomous vehicle from performing one or moreautonomous vehicle actions. For example, autonomous vehicle actions mayinclude accelerating, braking, turning an engine off, and turning theengine on, and/or the like.

FIGS. 8A-C depict diagrams 800 of a seating compartment 802 of anautonomous vehicle (e.g., autonomous vehicle 102) configured to presentinteractive content (e.g., interactive content 310) on an interiorsurface of the autonomous vehicle. The seating compartment includesseats 804A-B, windows 806A-B, and an interactive content projector 808.Although an interactive content projector 808 is shown here, interactivecontent may be presented otherwise. For example, the one or more of thewindows 806A-B may comprise an interactive content display devicecapable of displaying interactive content. For example, the interactivecontent projector 808 may project the interactive content 810-812 ontowindow 806A (FIG. 8B). In some embodiments, the interactive contentprojector 808 may project multi-layered images onto window 806A (FIG.8B-C) and/or the windows 806A-B may be capable of displayingmulti-layered images. The multi-layered images may bepresented/displayed/projected such that they appear as, and/or simulate,virtual reality, augmented reality, and/or the like. As discussedelsewhere herein, the interactive content may be adjusted, as opposed tobeing static and/or fixed. For example, the interactive content may berotated as the autonomous vehicle turns. In another example, theinteractive content may be adjusted in response to exterior conditions(e.g., terrain, time of day, etc.).

FIGS. 9 depicts a diagram 900 of a seating compartment 902 of anautonomous vehicle (e.g., autonomous vehicle 102) configured to detectuser behavior within the autonomous vehicle. The seating compartment 902includes smart seats 902A-B. In the example of FIG. 9, the smart seats902A-B each include tactile-sensitive surface material 904A-B coveringthe exterior of the seats 902A-B, and other sensors 906A-B, 908A-B, and910A-B. An additional other sensor 912 is disposed on a floor of theautonomous vehicle.

FIG. 10 depicts a diagram 1000 of a seating compartment 1002 of anautonomous vehicle (e.g., autonomous vehicle 102) configured to detectuser behavior within the autonomous vehicle and present interactivecontent (e.g., interactive content 310) on an interior surface of theautonomous vehicle. In the example of FIG. 10, the seating compartmentincludes smart seats 1002A-B including tactile-sensitive surfacematerial 1004A-B and other sensors 1006A-B, 1008A-B, and 1010A-B. Anadditional other sensor 1012 is disposed on a floor of the autonomousvehicle. An interactive content projector 1014 is mounted within theseating compartment projecting interactive content 1016 onto a window1018 of the autonomous vehicle. The window 1018 may be curved tofacilitate presentation of the interactive content 1016.

Hardware Implementation

The techniques described herein are implemented by one or morespecial-purpose computing devices. The special-purpose computing devicesmay be hard-wired to perform the techniques, or may include circuitry ordigital electronic devices such as one or more application-specificintegrated circuits (ASICs) or field programmable gate arrays (FPGAs)that are persistently programmed to perform the techniques, or mayinclude one or more hardware processors programmed to perform thetechniques pursuant to program instructions in firmware, memory, otherstorage, or a combination. Such special-purpose computing devices mayalso combine custom hard-wired logic, ASICs, or FPGAs with customprogramming to accomplish the techniques. The special-purpose computingdevices may be desktop computer systems, server computer systems,portable computer systems, handheld devices, networking devices or anyother device or combination of devices that incorporate hard-wiredand/or program logic to implement the techniques.

Computing device(s) are generally controlled and coordinated byoperating system software, such as iOS, Android, Chrome OS, Windows XP,Windows Vista, Windows 7, Windows 8, Windows Server, Windows CE, Unix,Linux, SunOS, Solaris, iOS, Blackberry OS, VxWorks, or other compatibleoperating systems. In other embodiments, the computing device may becontrolled by a proprietary operating system. Conventional operatingsystems control and schedule computer processes for execution, performmemory management, provide file system, networking, I/O services, andprovide a user interface functionality, such as a graphical userinterface (“GUI”), among other things.

FIG. 11 is a block diagram that illustrates a computer system 1100 uponwhich any of the embodiments described herein may be implemented. Thecomputer system 1100 includes a bus 1102 or other communicationmechanism for communicating information, one or more hardware processors1104 coupled with bus 1102 for processing information. Hardwareprocessor(s) 1104 may be, for example, one or more general purposemicroprocessors.

The computer system 1100 also includes a main memory 1106, such as arandom access memory (RAM), cache and/or other dynamic storage devices,coupled to bus 1102 for storing information and instructions to beexecuted by processor 1104. Main memory 1106 also may be used forstoring temporary variables or other intermediate information duringexecution of instructions to be executed by processor 1104. Suchinstructions, when stored in storage media accessible to processor 1104,render computer system 1100 into a special-purpose machine that iscustomized to perform the operations specified in the instructions.

The computer system 1100 further includes a read only memory (ROM) 1108or other static storage device coupled to bus 1102 for storing staticinformation and instructions for processor 1104. A storage device 1110,such as a magnetic disk, optical disk, or USB thumb drive (Flash drive),etc., is provided and coupled to bus 1102 for storing information andinstructions.

The computer system 1100 may be coupled via bus 1102 to output device(s)1112, such as a cathode ray tube (CRT) or LCD display (or touch screen),for displaying information to a computer user. Input device(s) 1114,including alphanumeric and other keys, are coupled to bus 1102 forcommunicating information and command selections to processor 1104.Another type of user input device is cursor control 1116, such as amouse, a trackball, or cursor direction keys for communicating directioninformation and command selections to processor 1104 and for controllingcursor movement on display 1112. This input device typically has twodegrees of freedom in two axes, a first axis (e.g., x) and a second axis(e.g., y), that allows the device to specify positions in a plane. Insome embodiments, the same direction information and command selectionsas cursor control may be implemented via receiving touches on a touchscreen without a cursor.

The computing system 1100 may include a user interface module toimplement a GUI that may be stored in a mass storage device asexecutable software codes that are executed by the computing device(s).This and other modules may include, by way of example, components, suchas software components, object-oriented software components, classcomponents and task components, processes, functions, attributes,procedures, subroutines, segments of program code, drivers, firmware,microcode, circuitry, data, databases, data structures, tables, arrays,and variables.

In general, the word “module,” as used herein, refers to logic embodiedin hardware or firmware, or to a collection of software instructions,possibly having entry and exit points, written in a programminglanguage, such as, for example, Java, C or C++. A software module may becompiled and linked into an executable program, installed in a dynamiclink library, or may be written in an interpreted programming languagesuch as, for example, BASIC, Perl, or Python. It will be appreciatedthat software modules may be callable from other modules or fromthemselves, and/or may be invoked in response to detected events orinterrupts. Software modules configured for execution on computingdevices may be provided on a computer readable medium, such as a compactdisc, digital video disc, flash drive, magnetic disc, or any othertangible medium, or as a digital download (and may be originally storedin a compressed or installable format that requires installation,decompression or decryption prior to execution). Such software code maybe stored, partially or fully, on a memory device of the executingcomputing device, for execution by the computing device. Softwareinstructions may be embedded in firmware, such as an EPROM. It will befurther appreciated that hardware modules may be comprised of connectedlogic units, such as gates and flip-flops, and/or may be comprised ofprogrammable units, such as programmable gate arrays or processors. Themodules or computing device functionality described herein arepreferably implemented as software modules, but may be represented inhardware or firmware. Generally, the modules described herein refer tological modules that may be combined with other modules or divided intosub-modules despite their physical organization or storage.

The computer system 1100 may implement the techniques described hereinusing customized hard-wired logic, one or more ASICs or FPGAs, firmwareand/or program logic which in combination with the computer systemcauses or programs computer system 1100 to be a special-purpose machine.According to one embodiment, the techniques herein are performed bycomputer system 1100 in response to processor(s) 1104 executing one ormore sequences of one or more instructions contained in main memory1106. Such instructions may be read into main memory 1106 from anotherstorage medium, such as storage device 1110. Execution of the sequencesof instructions contained in main memory 1106 causes processor(s) 1104to perform the process steps described herein. In alternativeembodiments, hard-wired circuitry may be used in place of or incombination with software instructions.

The term “non-transitory media,” and similar terms, as used hereinrefers to any media that store data and/or instructions that cause amachine to operate in a specific fashion. Such non-transitory media maycomprise non-volatile media and/or volatile media. Non-volatile mediaincludes, for example, optical or magnetic disks, such as storage device1110. Volatile media includes dynamic memory, such as main memory 606.Common forms of non-transitory media include, for example, a floppydisk, a flexible disk, hard disk, solid state drive, magnetic tape, orany other magnetic data storage medium, a CD-ROM, any other optical datastorage medium, any physical medium with patterns of holes, a RAM, aPROM, and EPROM, a FLASH-EPROM, NVRAM, any other memory chip orcartridge, and networked versions of the same.

Non-transitory media is distinct from but may be used in conjunctionwith transmission media. Transmission media participates in transferringinformation between non-transitory media. For example, transmissionmedia includes coaxial cables, copper wire and fiber optics, includingthe wires that comprise bus 1102. Transmission media can also take theform of acoustic or light waves, such as those generated duringradio-wave and infra-red data communications.

Various forms of media may be involved in carrying one or more sequencesof one or more instructions to processor 1104 for execution. Forexample, the instructions may initially be carried on a magnetic disk orsolid state drive of a remote computer. The remote computer can load theinstructions into its dynamic memory and send the instructions over atelephone line using a modem. A modem local to computer system 1100 canreceive the data on the telephone line and use an infra-red transmitterto convert the data to an infra-red signal. An infra-red detector canreceive the data carried in the infra-red signal and appropriatecircuitry can place the data on bus 1102. Bus 1102 carries the data tomain memory 1106, from which processor 1104 retrieves and executes theinstructions. The instructions received by main memory 1106 mayretrieves and executes the instructions. The instructions received bymain memory 1106 may optionally be stored on storage device 1110 eitherbefore or after execution by processor 1104.

The computer system 1100 also includes a communication interface 1118coupled to bus 1102. Communication interface 1118 provides a two-waydata communication coupling to one or more network links that areconnected to one or more local networks. For example, communicationinterface 1118 may be an integrated services digital network (ISDN)card, cable modem, satellite modem, or a modem to provide a datacommunication connection to a corresponding type of telephone line. Asanother example, communication interface 1118 may be a local areanetwork (LAN) card to provide a data communication connection to acompatible LAN (or WAN component to communicated with a WAN). Wirelesslinks may also be implemented. In any such implementation, communicationinterface 1118 sends and receives electrical, electromagnetic or opticalsignals that carry digital data streams representing various types ofinformation.

A network link typically provides data communication through one or morenetworks to other data devices. For example, a network link may providea connection through local network to a host computer or to dataequipment operated by an Internet Service Provider (ISP). The ISP inturn provides data communication services through the world wide packetdata communication network now commonly referred to as the “Internet”.Local network and Internet both use electrical, electromagnetic oroptical signals that carry digital data streams. The signals through thevarious networks and the signals on network link and throughcommunication interface 1118, which carry the digital data to and fromcomputer system 1100, are example forms of transmission media.

The computer system 1100 can send messages and receive data, includingprogram code, through the network(s), network link and communicationinterface 1118. In the Internet example, a server might transmit arequested code for an application program through the Internet, the ISP,the local network and the communication interface 1118.

The received code may be executed by processor 1104 as it is received,and/or stored in storage device 1110, or other non-volatile storage forlater execution.

Each of the processes, methods, and algorithms described in thepreceding sections may be embodied in, and fully or partially automatedby, code modules executed by one or more computer systems or computerprocessors comprising computer hardware. The processes and algorithmsmay be implemented partially or wholly in application-specificcircuitry.

The various features and processes described above may be usedindependently of one another, or may be combined in various ways. Allpossible combinations and sub-combinations are intended to fall withinthe scope of this disclosure. In addition, certain method or processblocks may be omitted in some implementations. The methods and processesdescribed herein are also not limited to any particular sequence, andthe blocks or states relating thereto can be performed in othersequences that are appropriate. For example, described blocks or statesmay be performed in an order other than that specifically disclosed, ormultiple blocks or states may be combined in a single block or state.The example blocks or states may be performed in serial, in parallel, orin some other manner. Blocks or states may be added to or removed fromthe disclosed example embodiments. The example systems and componentsdescribed herein may be configured differently than described. Forexample, elements may be added to, removed from, or rearranged comparedto the disclosed example embodiments.

Conditional language, such as, among others, “can,” “could,” “might,” or“may,” unless specifically stated otherwise, or otherwise understoodwithin the context as used, is generally intended to convey that certainembodiments include, while other embodiments do not include, certainfeatures, elements and/or steps. Thus, such conditional language is notgenerally intended to imply that features, elements and/or steps are inany way required for one or more embodiments or that one or moreembodiments necessarily include logic for deciding, with or without userinput or prompting, whether these features, elements and/or steps areincluded or are to be performed in any particular embodiment.

Any process descriptions, elements, or blocks in the flow diagramsdescribed herein and/or depicted in the attached figures should beunderstood as potentially representing modules, segments, or portions ofcode which include one or more executable instructions for implementingspecific logical functions or steps in the process. Alternateimplementations are included within the scope of the embodimentsdescribed herein in which elements or functions may be deleted, executedout of order from that shown or discussed, including substantiallyconcurrently or in reverse order, depending on the functionalityinvolved, as would be understood by those skilled in the art.

It should be emphasized that many variations and modifications may bemade to the above-described embodiments, the elements of which are to beunderstood as being among other acceptable examples. All suchmodifications and variations are intended to be included herein withinthe scope of this disclosure. The foregoing description details certainembodiments of the invention. It will be appreciated, however, that nomatter how detailed the foregoing appears in text, the invention can bepracticed in many ways. As is also stated above, it should be noted thatthe use of particular terminology when describing certain features oraspects of the invention should not be taken to imply that theterminology is being re-defined herein to be restricted to including anyspecific characteristics of the features or aspects of the inventionwith which that terminology is associated. The scope of the inventionshould therefore be construed in accordance with the appended claims andany equivalents thereof.

Engines, Components, and Logic

Certain embodiments are described herein as including logic or a numberof components, engines, or mechanisms. Engines may constitute eithersoftware engines (e.g., code embodied on a machine-readable medium) orhardware engines. A “hardware engine” is a tangible unit capable ofperforming certain operations and may be configured or arranged in acertain physical manner. In various example embodiments, one or morecomputer systems (e.g., a standalone computer system, a client computersystem, or a server computer system) or one or more hardware engines ofa computer system (e.g., a processor or a group of processors) may beconfigured by software (e.g., an application or application portion) asa hardware engine that operates to perform certain operations asdescribed herein.

In some embodiments, a hardware engine may be implemented mechanically,electronically, or any suitable combination thereof. For example, ahardware engine may include dedicated circuitry or logic that ispermanently configured to perform certain operations. For example, ahardware engine may be a special-purpose processor, such as aField-Programmable Gate Array (FPGA) or an Application SpecificIntegrated Circuit (ASIC). A hardware engine may also includeprogrammable logic or circuitry that is temporarily configured bysoftware to perform certain operations. For example, a hardware enginemay include software executed by a general-purpose processor or otherprogrammable processor. Once configured by such software, hardwareengines become specific machines (or specific components of a machine)uniquely tailored to perform the configured functions and are no longergeneral-purpose processors. It will be appreciated that the decision toimplement a hardware engine mechanically, in dedicated and permanentlyconfigured circuitry, or in temporarily configured circuitry (e.g.,configured by software) may be driven by cost and time considerations.

Accordingly, the phrase “hardware engine” should be understood toencompass a tangible entity, be that an entity that is physicallyconstructed, permanently configured (e.g., hardwired), or temporarilyconfigured (e.g., programmed) to operate in a certain manner or toperform certain operations described herein. As used herein,“hardware-implemented engine” refers to a hardware engine. Consideringembodiments in which hardware engines are temporarily configured (e.g.,programmed), each of the hardware engines need not be configured orinstantiated at any one instance in time. For example, where a hardwareengine comprises a general-purpose processor configured by software tobecome a special-purpose processor, the general-purpose processor may beconfigured as respectively different special-purpose processors (e.g.,comprising different hardware engines) at different times. Softwareaccordingly configures a particular processor or processors, forexample, to constitute a particular hardware engine at one instance oftime and to constitute a different hardware engine at a differentinstance of time.

Hardware engines can provide information to, and receive informationfrom, other hardware engines. Accordingly, the described hardwareengines may be regarded as being communicatively coupled. Where multiplehardware engines exist contemporaneously, communications may be achievedthrough signal transmission (e.g., over appropriate circuits and buses)between or among two or more of the hardware engines. In embodiments inwhich multiple hardware engines are configured or instantiated atdifferent times, communications between such hardware engines may beachieved, for example, through the storage and retrieval of informationin memory structures to which the multiple hardware engines have access.For example, one hardware engine may perform an operation and store theoutput of that operation in a memory device to which it iscommunicatively coupled. A further hardware engine may then, at a latertime, access the memory device to retrieve and process the storedoutput. Hardware engines may also initiate communications with input oroutput devices, and can operate on a resource (e.g., a collection ofinformation).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented enginesthat operate to perform one or more operations or functions describedherein. As used herein, “processor-implemented engine” refers to ahardware engine implemented using one or more processors.

Similarly, the methods described herein may be at least partiallyprocessor-implemented, with a particular processor or processors beingan example of hardware. For example, at least some of the operations ofa method may be performed by one or more processors orprocessor-implemented engines. Moreover, the one or more processors mayalso operate to support performance of the relevant operations in a“cloud computing” environment or as a “software as a service” (SaaS).For example, at least some of the operations may be performed by a groupof computers (as examples of machines including processors), with theseoperations being accessible via a network (e.g., the Internet) and viaone or more appropriate interfaces (e.g., an Application ProgramInterface (API)).

The performance of certain of the operations may be distributed amongthe processors, not only residing within a single machine, but deployedacross a number of machines. In some example embodiments, the processorsor processor-implemented engines may be located in a single geographiclocation (e.g., within a home environment, an office environment, or aserver farm). In other example embodiments, the processors orprocessor-implemented engines may be distributed across a number ofgeographic locations.

Language

Throughout this specification, plural instances may implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations may be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures andfunctionality presented as separate components in example configurationsmay be implemented as a combined structure or component. Similarly,structures and functionality presented as a single component may beimplemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Although an overview of the subject matter has been described withreference to specific example embodiments, various modifications andchanges may be made to these embodiments without departing from thebroader scope of embodiments of the present disclosure. Such embodimentsof the subject matter may be referred to herein, individually orcollectively, by the term “invention” merely for convenience and withoutintending to voluntarily limit the scope of this application to anysingle disclosure or concept if more than one is, in fact, disclosed.

The embodiments illustrated herein are described in sufficient detail toenable those skilled in the art to practice the teachings disclosed.Other embodiments may be used and derived therefrom, such thatstructural and logical substitutions and changes may be made withoutdeparting from the scope of this disclosure. The Detailed Description,therefore, is not to be taken in a limiting sense, and the scope ofvarious embodiments is defined only by the appended claims, along withthe full range of equivalents to which such claims are entitled.

It will be appreciated that an “engine,” “system,” “data store,” and/or“database” may comprise software, hardware, firmware, and/or circuitry.In one example, one or more software programs comprising instructionscapable of being executable by a processor may perform one or more ofthe functions of the engines, data stores, databases, or systemsdescribed herein. In another example, circuitry may perform the same orsimilar functions. Alternative embodiments may comprise more, less, orfunctionally equivalent engines, systems, data stores, or databases, andstill be within the scope of present embodiments. For example, thefunctionality of the various systems, engines, data stores, and/ordatabases may be combined or divided differently.

“Open source” software is defined herein to be source code that allowsdistribution as source code as well as compiled form, with awell-publicized and indexed means of obtaining the source, optionallywith a license that allows modifications and derived works.

The data stores described herein may be any suitable structure (e.g., anactive database, a relational database, a self-referential database, atable, a matrix, an array, a flat file, a documented-oriented storagesystem, a non-relational No-SQL system, and the like), and may becloud-based or otherwise.

As used herein, the term “or” may be construed in either an inclusive orexclusive sense. Moreover, plural instances may be provided forresources, operations, or structures described herein as a singleinstance. Additionally, boundaries between various resources,operations, engines, engines, and data stores are somewhat arbitrary,and particular operations are illustrated in a context of specificillustrative configurations. Other allocations of functionality areenvisioned and may fall within a scope of various embodiments of thepresent disclosure. In general, structures and functionality presentedas separate resources in the example configurations may be implementedas a combined structure or resource. Similarly, structures andfunctionality presented as a single resource may be implemented asseparate resources. These and other variations, modifications,additions, and improvements fall within a scope of embodiments of thepresent disclosure as represented by the appended claims. Thespecification and drawings are, accordingly, to be regarded in anillustrative rather than a restrictive sense.

Conditional language, such as, among others, “can,” “could,” “might,” or“may,” unless specifically stated otherwise, or otherwise understoodwithin the context as used, is generally intended to convey that certainembodiments include, while other embodiments do not include, certainfeatures, elements and/or steps. Thus, such conditional language is notgenerally intended to imply that features, elements and/or steps are inany way required for one or more embodiments or that one or moreembodiments necessarily include logic for deciding, with or without userinput or prompting, whether these features, elements and/or steps areincluded or are to be performed in any particular embodiment.

Although the invention(s) have been described in detail for the purposeof illustration based on what is currently considered to be the mostpractical and preferred implementations, it is to be understood thatsuch detail is solely for that purpose and that the invention is notlimited to the disclosed implementations, but, on the contrary, isintended to cover modifications and equivalent arrangements that arewithin the spirit and scope of the appended claims. For example, it isto be understood that the present invention contemplates that, to theextent possible, one or more features of any embodiment can be combinedwith one or more features of any other embodiment.

The foregoing description of the present invention(s) have been providedfor the purposes of illustration and description. It is not intended tobe exhaustive or to limit the invention to the precise forms disclosed.The breadth and scope of the present invention should not be limited byany of the above-described exemplary embodiments. Many modifications andvariations will be apparent to the practitioner skilled in the art. Themodifications and variations include any relevant combination of thedisclosed features. The embodiments were chosen and described in orderto best explain the principles of the invention and its practicalapplication, thereby enabling others skilled in the art to understandthe invention for various embodiments and with various modificationsthat are suited to the particular use contemplated. It is intended thatthe scope of the invention be defined by the following claims and theirequivalence.

The invention claimed is:
 1. A system comprising: one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the system to perform: obtaining smart seat sensor data, the smart seat sensor data being detected by a tactile-sensitive surface material of a seat of a vehicle in response to an occupant interacting with the tactile-sensitive surface material and wherein the smart seat sensor data is indicative of a particular type of movement of the occupant as detected by the tactile-sensitive surface material of the seat; obtaining other sensor data from one or more other sensors disposed within the vehicle; integrating the smart seat sensor data and the other sensor data; estimating a behavior of the occupant based on the integrated data, wherein the estimated behavior comprises a physical movement of the occupant; and controlling the vehicle based on the estimated behavior of the occupant.
 2. The system of claim 1, wherein the occupant interacting with the tactile-sensitive surface material comprises a passenger sitting on the seat of the vehicle.
 3. The system of claim 1, wherein the behavior of the occupant is estimated using a machine learning model.
 4. The system of claim 3, wherein integrating the smart seat sensor data and the other sensor data includes creating a new dataset in accordance with the machine learning model.
 5. The system of claim 1, wherein the estimated behavior further comprises any of the occupant entering the vehicle, the occupant exiting the vehicle, the occupant damaging the vehicle, and the occupant leaving an object in the vehicle subsequent to the occupant exiting the vehicle.
 6. The system of claim 1, wherein the one or more other sensors are disposed within any of a headrest portion of the seat of the vehicle, a backrest portion of the seat, a sitting portion of the seat of the vehicle, a floor portion of the vehicle, a roof portion of the vehicle, and a door portion of the vehicle.
 7. The system of claim 1, wherein controlling the vehicle comprises any allowing the vehicle to perform one or more vehicle actions, and preventing the vehicle from performing the one or more vehicle actions.
 8. The system of claim 7, wherein the one or more vehicle actions include any of accelerating, braking, turning an engine of the vehicle off, and turning the engine of the vehicle on.
 9. The system of claim 1, wherein the smart seat sensor data indicates whether the occupant is asleep.
 10. The system of claim 1, wherein the other sensors are integrated with the vehicle and disposed on any of a seat, a floor, a ceiling, or a door of the vehicle.
 11. The system of claim 1, wherein the other sensors exclude cameras.
 12. The system of claim 1, wherein the instructions further cause the system to perform rotating a presentation of interactive content and adjusting a playback speed of the interactive content on a window in anticipation of a predicted steering action on the vehicle and based on the estimated behavior of the occupant.
 13. A method being implemented by a computing system including one or more physical processors and storage media storing machine-readable instructions, the method comprising: obtaining smart seat sensor data, the smart seat sensor data being detected by a tactile-sensitive surface material of a seat of an vehicle in response to an occupant interacting with the tactile-sensitive surface material and wherein the smart seat sensor data is indicative of a particular type of movement of the occupant as detected by the tactile-sensitive surface material of the seat; obtaining other sensor data from one or more other sensors disposed within the vehicle; integrating the smart seat sensor data and the other sensor data; estimating a behavior of the occupant based on the integrated data, wherein the estimated behavior comprises a physical movement of the occupant; and controlling the vehicle based on the estimated behavior of the occupant.
 14. The method of claim 13, wherein the occupant interacting with the tactile-sensitive surface material comprises a passenger sitting on the seat of the vehicle.
 15. The method of claim 13, wherein the behavior of the occupant is estimated using a machine learning model.
 16. The method of claim 15, wherein integrating the smart seat sensor data and the other sensor data includes creating a new dataset in accordance with the machine learning model.
 17. The method of claim 13, wherein the estimated behavior further comprises any of the occupant entering the vehicle, the occupant exiting the vehicle, the occupant damaging the vehicle, and the occupant leaving an object in the vehicle subsequent to the occupant exiting the vehicle.
 18. The method of claim 13, wherein controlling the vehicle comprises any allowing the vehicle to perform one or more vehicle actions, and preventing the vehicle from performing the one or more vehicle actions.
 19. The method of claim 18, wherein the one or more vehicle actions include any of accelerating, braking, turning an engine of the vehicle off, and turning the engine of the vehicle on.
 20. A non-transitory computer readable medium comprising instructions that, when executed, cause one or more processors to perform: obtaining smart seat sensor data, the smart seat sensor data being detected by a tactile-sensitive surface material of a seat of vehicle in response to an occupant interacting with the tactile-sensitive surface material and wherein the smart seat sensor data is indicative of a particular type of movement of the occupant as detected by the tactile-sensitive surface material of the seat; obtaining other sensor data from one or more other sensors disposed within the vehicle; integrating the smart seat sensor data and the other sensor data; estimating a behavior of the occupant based on the integrated data, wherein the estimated behavior comprises a physical movement of the occupant; and controlling the vehicle based on the estimated behavior of the occupant. 